regularizer.py 2.0 KB
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# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals

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import paddle
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class L1Decay(object):
    """
    L1 Weight Decay Regularization, which encourages the weights to be sparse.
    Args:
        factor(float): regularization coeff. Default:0.0.
    """

    def __init__(self, factor=0.0):
        super(L1Decay, self).__init__()
        self.regularization_coeff = factor

    def __call__(self):
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        reg = paddle.regularizer.L1Decay(self.regularization_coeff)
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        return reg


class L2Decay(object):
    """
    L2 Weight Decay Regularization, which encourages the weights to be sparse.
    Args:
        factor(float): regularization coeff. Default:0.0.
    """

    def __init__(self, factor=0.0):
        super(L2Decay, self).__init__()
        self.regularization_coeff = factor

    def __call__(self):
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        reg = paddle.regularizer.L2Decay(self.regularization_coeff)
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        return reg
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class ConstDecay(object):
    """
    Const L2 Weight Decay Regularization, which encourages the weights to be sparse.
    Args:
        factor(float): regularization coeff. Default:0.0.
    """

    def __init__(self, factor=0.0):
        super(ConstDecay, self).__init__()
        self.regularization_coeff = factor

    def __call__(self):
        return self.regularization_coeff